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两个matlab实现的K-MEANS聚类算法

于 2021-05-07 发布
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代码说明:

%k-means 算法接受输入量 k ;然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足:%同一聚类中的对象相似度较高;而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”(引力中心)来进行计算的。%k-means 算法的工作过程说明如下:首先从n个数据对象任意选择 k 个对象作为初始聚类中心;而对于所剩下其它对象,%则根据它们与这些聚类中心的相似度(距离),分别将它们分配给与其最相似的(聚类中心所代表的)聚类;%然后再计算每个所获新聚类的聚类中心(该聚类中所有对象的均值);%不断重复这一过程直到标准测度函数开始收敛为止。一般都采用均方差作

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